3D Mapping of Indoor Parking Space Using Edge Consistency Census Transform Stereo Odometry

초록

In this paper, we propose a real-time 3D mapping system for indoor parking ramps and spaces. Visual odometry is calculated by applying the proposed Edge Consistency Census Transform (ECCT) stereo matching method. ECCT works strongly in repeated patterns and reduces drift errors in the vertical direction of the ground caused by Kanade-Lucas-Tomasi stereo matching of VINS-FUSION algorithm. We propose a mobile mapping system that uses a stereo camera and 2D lidar for data set acquisition. The parking ramp and spaces dataset are obtained using the mobile mapping system and are reconstructed using the proposed system. The proposed system performs the 3D mapping of the parking ramp and spaces dataset that is obtained using the mobile mapping system. We present the error of the normal vector with respect to the ground of the parking space as a quantitative evaluation for performance comparison with the previous method. Also, we present 3D mapping results as qualitative results. © 2022 by SCITEPRESS-Science and Technology Publications, Lda.

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